Lectures In Parallel Computation

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Lectures In Parallel Computation

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Author : Alan Gibbons
language : en
Publisher: Cambridge University Press
Release Date : 1993-03-18

Lectures In Parallel Computation written by Alan Gibbons and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1993-03-18 with Computers categories.

The foundations of parallel computation, especially the efficiency of computation, are the concern of this book. Distinguished international researchers have contributed fifteen chapters which together form a coherent stream taking the reader who has little prior knowledge of the field to a position of being familiar with leading edge issues. The book may also function as a source of teaching material and reference for researchers. The first part is devoted to the Parallel Random Access Machine (P-RAM) model of parallel computation. The initial chapters justify and define the model, which is then used for the development of algorithm design in a variety of application areas such as deterministic algorithms, randomisation and algorithm resilience. The second part deals with distributed memory models of computation. The question of efficiently implementing P-RAM algorithms within these models is addressed as are the immensely interesting prospects for general purpose parallel computation.

Introduction To Parallel Computing

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Author : Wesley Petersen
language : en
Publisher: OUP Oxford
Release Date : 2004-01-08

Introduction To Parallel Computing written by Wesley Petersen and has been published by OUP Oxford this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-01-08 with Computers categories.

In the last few years, courses on parallel computation have been developed and offered in many institutions in the UK, Europe and US as a recognition of the growing significance of this topic in mathematics and computer science. There is a clear need for texts that meet the needs of students and lecturers and this book, based on the author's lecture at ETH Zurich, is an ideal practical student guide to scientific computing on parallel computers working up from a hardware instruction level, to shared memory machines, and finally to distributed memory machines. Aimed at advanced undergraduate and graduate students in applied mathematics, computer science, and engineering, subjects covered include linear algebra, fast Fourier transform, and Monte-Carlo simulations, including examples in C and, in some cases, Fortran. This book is also ideal for practitioners and programmers.

Scheduling For Parallel Processing

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Author : Maciej Drozdowski
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-03-14

Scheduling For Parallel Processing written by Maciej Drozdowski and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-03-14 with Computers categories.

Overview and Goals This book is dedicated to scheduling for parallel processing. Presenting a research ?eld as broad as this one poses considerable dif?culties. Scheduling for parallel computing is an interdisciplinary subject joining many ?elds of science and te- nology. Thus, to understand the scheduling problems and the methods of solving them it is necessary to know the limitations in related areas. Another dif?culty is that the subject of scheduling parallel computations is immense. Even simple search in bibliographical databases reveals thousands of publications on this topic. The - versity in understanding scheduling problems is so great that it seems impossible to juxtapose them in one scheduling taxonomy. Therefore, most of the papers on scheduling for parallel processing refer to one scheduling problem resulting from one way of perceiving the reality. Only a few publications attempt to arrange this ?eld of knowledge systematically. In this book we will follow two guidelines. One guideline is a distinction - tween scheduling models which comprise a set of scheduling problems solved by dedicated algorithms. Thus, the aim of this book is to present scheduling models for parallel processing, problems de?ned on the grounds of certain scheduling models, and algorithms solving the scheduling problems. Most of the scheduling problems are combinatorial in nature. Therefore, the second guideline is the methodology of computational complexity theory. Inthisbookwepresentfourexamplesofschedulingmodels. Wewillgodeepinto the models, problems, and algorithms so that after acquiring some understanding of them we will attempt to draw conclusions on their mutual relationships.

Lectures In Parallel Computation

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Author : Alan Gibbons
language : en
Publisher: Cambridge University Press
Release Date : 2005-07-21

Lectures In Parallel Computation written by Alan Gibbons and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-07-21 with Computers categories.

This book contains collected lectures given at the 1990 ALCOM Spring School of Parallel Computation. The motivation for the school was to provide an introduction for graduate students to topics at the leading edge of research in this very active area of computer science. Topics covered include PRAM algorithmics, general purpose computation, systolic and distributed algorithms, distributed memory models, as well as issues from practical parallel computation. The papers by some of the leading figures in this field have been carefully edited to make a coherent and unique introduction to the state of the art in concurrent computing.

An Introduction To Parallel Programming

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Author : Peter Pacheco
language : en
Publisher: Morgan Kaufmann
Release Date : 2021-08-27

An Introduction To Parallel Programming written by Peter Pacheco and has been published by Morgan Kaufmann this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-27 with Computers categories.

An Introduction to Parallel Programming, Second Edition presents a tried-and-true tutorial approach that shows students how to develop effective parallel programs with MPI, Pthreads and OpenMP.As the first undergraduate text to directly address compiling and running parallel programs on multi-core and cluster architecture, this second edition carries forward its clear explanations for designing, debugging and evaluating the performance of distributed and shared-memory programs while adding coverage of accelerators via new content on GPU programming and heterogeneous programming. New and improved user-friendly exercises teach students how to compile, run and modify example programs. - Takes a tutorial approach, starting with small programming examples and building progressively to more challenging examples - Explains how to develop parallel programs using MPI, Pthreads and OpenMP programming models - A robust package of online ancillaries for instructors and students includes lecture slides, solutions manual, downloadable source code, and an image bank New to this edition: - New chapters on GPU programming and heterogeneous programming - New examples and exercises related to parallel algorithms

Parallel And High Performance Computing

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Author : Robert Robey
language : en
Publisher: Simon and Schuster
Release Date : 2021-08-24

Parallel And High Performance Computing written by Robert Robey and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-24 with Computers categories.

Parallel and High Performance Computing offers techniques guaranteed to boost your code’s effectiveness. Summary Complex calculations, like training deep learning models or running large-scale simulations, can take an extremely long time. Efficient parallel programming can save hours—or even days—of computing time. Parallel and High Performance Computing shows you how to deliver faster run-times, greater scalability, and increased energy efficiency to your programs by mastering parallel techniques for multicore processor and GPU hardware. About the technology Write fast, powerful, energy efficient programs that scale to tackle huge volumes of data. Using parallel programming, your code spreads data processing tasks across multiple CPUs for radically better performance. With a little help, you can create software that maximizes both speed and efficiency. About the book Parallel and High Performance Computing offers techniques guaranteed to boost your code’s effectiveness. You’ll learn to evaluate hardware architectures and work with industry standard tools such as OpenMP and MPI. You’ll master the data structures and algorithms best suited for high performance computing and learn techniques that save energy on handheld devices. You’ll even run a massive tsunami simulation across a bank of GPUs. What's inside Planning a new parallel project Understanding differences in CPU and GPU architecture Addressing underperforming kernels and loops Managing applications with batch scheduling About the reader For experienced programmers proficient with a high-performance computing language like C, C++, or Fortran. About the author Robert Robey works at Los Alamos National Laboratory and has been active in the field of parallel computing for over 30 years. Yuliana Zamora is currently a PhD student and Siebel Scholar at the University of Chicago, and has lectured on programming modern hardware at numerous national conferences. Table of Contents PART 1 INTRODUCTION TO PARALLEL COMPUTING 1 Why parallel computing? 2 Planning for parallelization 3 Performance limits and profiling 4 Data design and performance models 5 Parallel algorithms and patterns PART 2 CPU: THE PARALLEL WORKHORSE 6 Vectorization: FLOPs for free 7 OpenMP that performs 8 MPI: The parallel backbone PART 3 GPUS: BUILT TO ACCELERATE 9 GPU architectures and concepts 10 GPU programming model 11 Directive-based GPU programming 12 GPU languages: Getting down to basics 13 GPU profiling and tools PART 4 HIGH PERFORMANCE COMPUTING ECOSYSTEMS 14 Affinity: Truce with the kernel 15 Batch schedulers: Bringing order to chaos 16 File operations for a parallel world 17 Tools and resources for better code

Encyclopedia Of Parallel Computing

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Author : David Padua
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-09-08

Encyclopedia Of Parallel Computing written by David Padua and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-09-08 with Computers categories.

Containing over 300 entries in an A-Z format, the Encyclopedia of Parallel Computing provides easy, intuitive access to relevant information for professionals and researchers seeking access to any aspect within the broad field of parallel computing. Topics for this comprehensive reference were selected, written, and peer-reviewed by an international pool of distinguished researchers in the field. The Encyclopedia is broad in scope, covering machine organization, programming languages, algorithms, and applications. Within each area, concepts, designs, and specific implementations are presented. The highly-structured essays in this work comprise synonyms, a definition and discussion of the topic, bibliographies, and links to related literature. Extensive cross-references to other entries within the Encyclopedia support efficient, user-friendly searchers for immediate access to useful information. Key concepts presented in the Encyclopedia of Parallel Computing include; laws and metrics; specific numerical and non-numerical algorithms; asynchronous algorithms; libraries of subroutines; benchmark suites; applications; sequential consistency and cache coherency; machine classes such as clusters, shared-memory multiprocessors, special-purpose machines and dataflow machines; specific machines such as Cray supercomputers, IBM’s cell processor and Intel’s multicore machines; race detection and auto parallelization; parallel programming languages, synchronization primitives, collective operations, message passing libraries, checkpointing, and operating systems. Topics covered: Speedup, Efficiency, Isoefficiency, Redundancy, Amdahls law, Computer Architecture Concepts, Parallel Machine Designs, Benmarks, Parallel Programming concepts & design, Algorithms, Parallel applications. This authoritative reference will be published in two formats: print and online. The online edition features hyperlinks to cross-references and to additional significant research. Related Subjects: supercomputing, high-performance computing, distributed computing

Feynman Lectures On Computation

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Author : Tony Hey
language : en
Publisher: CRC Press
Release Date : 2023-05-18

Feynman Lectures On Computation written by Tony Hey and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-05-18 with Science categories.

The last lecture course that Nobel Prize winner Richard P. Feynman gave to students at Caltech from 1983 to 1986 was not on physics but on computer science. The first edition of the Feynman Lectures on Computation, published in 1996, provided an overview of standard and not-so-standard topics in computer science given in Feynman’s inimitable style. Although now over 20 years old, most of the material is still relevant and interesting, and Feynman’s unique philosophy of learning and discovery shines through. For this new edition, Tony Hey has updated the lectures with an invited chapter from Professor John Preskill on “Quantum Computing 40 Years Later”. This contribution captures the progress made toward building a quantum computer since Feynman’s original suggestions in 1981. The last 25 years have also seen the “Moore’s law” roadmap for the IT industry coming to an end. To reflect this transition, John Shalf, Senior Scientist at Lawrence Berkeley National Laboratory, has contributed a chapter on “The Future of Computing beyond Moore’s Law”. The final update for this edition is an attempt to capture Feynman’s interest in artificial intelligence and artificial neural networks. Eric Mjolsness, now a Professor of Computer Science at the University of California Irvine, was a Teaching Assistant for Feynman’s original lecture course and his research interests are now the application of artificial intelligence and machine learning for multi-scale science. He has contributed a chapter called “Feynman on Artificial Intelligence and Machine Learning” that captures the early discussions with Feynman and also looks toward future developments. This exciting and important work provides key reading for students and scholars in the fields of computer science and computational physics.

Programming Massively Parallel Processors

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Author : David B. Kirk
language : en
Publisher: Newnes
Release Date : 2012-12-31

Programming Massively Parallel Processors written by David B. Kirk and has been published by Newnes this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-31 with Computers categories.

Programming Massively Parallel Processors: A Hands-on Approach, Second Edition, teaches students how to program massively parallel processors. It offers a detailed discussion of various techniques for constructing parallel programs. Case studies are used to demonstrate the development process, which begins with computational thinking and ends with effective and efficient parallel programs. This guide shows both student and professional alike the basic concepts of parallel programming and GPU architecture. Topics of performance, floating-point format, parallel patterns, and dynamic parallelism are covered in depth. This revised edition contains more parallel programming examples, commonly-used libraries such as Thrust, and explanations of the latest tools. It also provides new coverage of CUDA 5.0, improved performance, enhanced development tools, increased hardware support, and more; increased coverage of related technology, OpenCL and new material on algorithm patterns, GPU clusters, host programming, and data parallelism; and two new case studies (on MRI reconstruction and molecular visualization) that explore the latest applications of CUDA and GPUs for scientific research and high-performance computing. This book should be a valuable resource for advanced students, software engineers, programmers, and hardware engineers. - New coverage of CUDA 5.0, improved performance, enhanced development tools, increased hardware support, and more - Increased coverage of related technology, OpenCL and new material on algorithm patterns, GPU clusters, host programming, and data parallelism - Two new case studies (on MRI reconstruction and molecular visualization) explore the latest applications of CUDA and GPUs for scientific research and high-performance computing

Introduction To Parallel Computing

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Author : Roman Trobec
language : en
Publisher:
Release Date : 2018

Introduction To Parallel Computing written by Roman Trobec and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018 with Parallel processing (Electronic computers) categories.

Advancements in microprocessor architecture, interconnection technology, and software development have fueled rapid growth in parallel and distributed computing. However, this development is only of practical benefit if it is accompanied by progress in the design, analysis and programming of parallel algorithms. This concise textbook provides, in one place, three mainstream parallelization approaches, Open MPP, MPI and OpenCL, for multicore computers, interconnected computers and graphical processing units. An overview of practical parallel computing and principles will enable the reader to design efficient parallel programs for solving various computational problems on state-of-the-art personal computers and computing clusters. Topics covered range from parallel algorithms, programming tools, OpenMP, MPI and OpenCL, followed by experimental measurements of parallel programs' run-times, and by engineering analysis of obtained results for improved parallel execution performances. Many examples and exercises support the exposition.